Date column shifts and is no longer callable - pandas

Question

I am using pandas groupby to group duplicate dates by their pm25 values to get one average. However when I use the groupby function, the structure of my dataframe changes, and I can no longer call the 'Date' Column.
Using groupby also changes the structure of my data: instead of being sorted by 1/1/19, 1/2/19, it is sorted by 1/1/19, 1/10/19, 1/11/19.
Here is my current code:
Before using df.groupby my df looks like:
df before groupy
I use groupby:
df.groupby('Date').mean('pm25')
print(df)
df after groupby
And after, I cannot call the 'Date' column anymore or sort the column
print(df['Date'])
Returns just
KeyError: 'Date'
Please help, or please let me know what else I can provide.

Answer 1

Using groupby also changes the structure of my data: instead of being sorted by 1/1/19, 1/2/19, it is sorted by 1/1/19, 1/10/19, 1/11/19.
This is because your Date column type is string not datetime. In string comparison, the third character 1 of 1/10/19 is smaller than the third character 2 of 1/2/19. If you want to keep the original sequence, you can to the following
df['Date'] = pd.to_datetime(df['Date']) # Convert Date column to datetime type
df['Date'] = df['Date'].dt.strftime('%m/%d/%y') # Convert datetime to other formats (but the dtype of column will be string)
And after, I cannot call the 'Date' column anymore or sort the column
This is because after groupby Date column, the returned dataframe will use Date column after groupby as index to represent each group.
pm25
Date
01/01/19 8.50
01/02/19 9.20
01/03/19 7.90
01/04/19 8.90
01/05/19 6.00
After doing df.groupby('Date').mean('pm25'), the returned dataframe above means the mean pm25 value of 01/01/19 group is 8.50, etc.
If you want to retrieve the Date column back from the index, you can reset_index() after groupby,
df.groupby('Date').mean('pm25').reset_index()
which gives
Date pm25
0 01/01/19 8.50
1 01/02/19 9.20
2 01/03/19 7.90
3 01/04/19 8.90
4 01/05/19 6.00
5 01/06/19 6.75
6 01/11/19 8.50
7 01/12/19 9.20
8 01/21/19 9.20
Or specify the as_index argument of pandas.DataFrame.groupby() to False
df.groupby('Date', as_index=False).mean('pm25')